Department of Ophthalmology, São Paulo Federal University, São Paulo, SP, Brazil; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
Department of Ophthalmology, São Paulo Federal University, São Paulo, SP, Brazil.
Surv Ophthalmol. 2023 Jul-Aug;68(4):669-677. doi: 10.1016/j.survophthal.2023.02.007. Epub 2023 Mar 4.
Uveitis is a disease complex characterized by intraocular inflammation of the uvea that is an important cause of blindness and social morbidity. With the dawn of artificial intelligence (AI) and machine learning integration in health care, their application in uveitis creates an avenue to improve screening and diagnosis. Our review identified the use of artificial intelligence in studies of uveitis and classified them as diagnosis support, finding detection, screening, and standardization of uveitis nomenclature. The overall performance of models is poor, with limited datasets and a lack of validation studies and publicly available data and codes. We conclude that AI holds great promise to assist with the diagnosis and detection of ocular findings of uveitis, but further studies and large representative datasets are needed to guarantee generalizability and fairness.
葡萄膜炎是一种以眼内葡萄膜炎症为特征的疾病，是导致失明和社会发病率的重要原因。随着人工智能（AI）和机器学习在医疗保健中的融合，它们在葡萄膜炎中的应用为改善筛查和诊断提供了途径。我们的综述确定了人工智能在葡萄膜炎研究中的应用，并将其分为诊断支持、发现检测、筛查和葡萄膜炎命名法的标准化。模型的整体性能较差，数据集有限，缺乏验证研究以及公开的数据和代码。我们的结论是，人工智能在协助诊断和检测葡萄膜炎的眼部表现方面具有巨大的潜力，但需要进一步的研究和大型代表性数据集来保证泛化性和公平性。
